Lead AI Engineer

The Lead, AI Engineer is a senior role responsible for designing, building, and deploying next-generation AI systems that enable Boost Bank's transformation into an AI-driven digital bank.

This includes leading Generative AI (GenAI), Large Language Model (LLM), and Agentic AI initiatives across customer onboarding, transactional automation, risk intelligence, and product personalization.

The role requires both strategic vision and hands-on technical depth — blending AI research, system architecture, and delivery leadership. The incumbent will collaborate with cross-functional teams (Product, Risk, Operations, Technology) to embed intelligence and automation into every process, while ensuring responsible, compliant, and scalable AI deployment.

Day to Day Responsibility:

• Design and Deliver AI Systems:

Architect and lead development of LLM-powered and Agentic AI systems for transactional, onboarding, and customer service use cases. Develop and integrate agentic workflows for onboarding, payments, and customer support use cases. Optimize model performance, latency, and safety for real-time transactional experiences.

• Research and Experimentation:

Conduct applied research in Generative AI, fine-tuning models for banking language, tone, and safety. Develop and evaluate RAG pipelines, embeddings, and prompt-engineering strategies. Translate research outcomes into scalable prototypes and production features.

• MLOps and Infrastructure Integration:

Partner with Data Engineering and DevOps teams to operationalize models using CI/CD pipelines, model registry, and drift monitoring. Optimize for latency, accuracy, and cost-efficiency in real-time applications. Ensure end-to-end observability, explainability, and compliance with internal AI governance frameworks.

• Collaboration and Leadership:

Lead a small team of AI Scientists/Engineers, guiding them in GenAI and LLM experimentation. Work with Product, Risk, and Ops teams to identify high-impact AI use cases aligned to business strategies. Represent Boost Bank's AI capabilities in Axiata Group and industry working groups. Mentor data and tech colleagues to elevate AI literacy across the organization.

• Governance and Responsible AI:

Implement Responsible AI controls, safety filters, audit logs, consent validation, and explainability. Document model design, assumptions, and evaluations for model approval. Ensure adherence to regulatory and ethical AI standards.

Need to Know (Knowledge & Skills):

• Deep expertise in AI , ML and modern AI architectures, particularly in applying the to real world business problems.
• Strong grasp of Generative AI concepts, including conversational AI, Large Language models and agentic systems.
• Skilled in Python, API development, and cloud AI services (AWS Bedrock, Azure OpenAI, Databricks).
• Understanding of data privacy, model governance, and BNM / PDPA compliance.
• Familiarity with AI evaluation metrics factuality, toxicity, hallucination, and coherence.
• Knowledge of banking or fintech ecosystems (lending, payments, onboarding) is a plus.

Need to Be (Attributes & Competencies):

• Innovative and research-oriented: curious to explore cutting-edge GenAI techniques and apply them pragmatically.
• Delivery-focused: able to balance experimentation with business impact and deadlines.
• Strategic thinker: able to align AI work with Boost Bank's business objectives.
• Clear Communicator: capable of translating AI concepts into business outcomes for senior stakeholders.
• Mentor and Team builder: Passionate about nurturing AI talent and fostering a culture of experimenting and Learning

Job Requirements:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.
• Advanced degree (Master's/PhD) in AI, Machine Learning or a quantitative discipline is an advantage.
• Minimum 8 years' experience in AI, machine learning, or data driven product engineering, including at least 2-3 years in a lead role.
• Proven experience in leading AI solution development from research to production.
• Experience in financial services, fintech, or large scale digital platform will be a distinct advantage.